Skip to content

Fix Issue #345: KeypointDetectionModel returns correct prediction type #428

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Open
kadhirash wants to merge 1 commit into
base: main
Choose a base branch
from
Open

Fix Issue #345: KeypointDetectionModel returns correct prediction type #428

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
3 changes: 3 additions & 0 deletions roboflow/config.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -71,8 +71,11 @@ def get_conditional_configuration_variable(key, default):
TYPE_OBJECT_DETECTION = "object-detection"
TYPE_INSTANCE_SEGMENTATION = "instance-segmentation"
TYPE_SEMANTIC_SEGMENTATION = "semantic-segmentation"
TYPE_SEMANTIC_SEGMENTATION = "semantic-segmentation"
TYPE_KEYPOINT_DETECTION = "keypoint-detection"

KEYPOINT_DETECTION_MODEL = "KeypointDetectionModel"

DEFAULT_BATCH_NAME = "Pip Package Upload"
DEFAULT_JOB_NAME = "Annotated via API"

Expand Down
4 changes: 2 additions & 2 deletions roboflow/models/keypoint_detection.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -8,7 +8,7 @@
import requests
from PIL import Image

from roboflow.config import CLASSIFICATION_MODEL
from roboflow.config import KEYPOINT_DETECTION_MODEL
from roboflow.models.inference import InferenceModel
from roboflow.util.image_utils import check_image_url
from roboflow.util.prediction import PredictionGroup
Expand Down Expand Up @@ -119,7 +119,7 @@ def predict(self, image_path, hosted=False, confidence=None): # type: ignore[ov
resp.json(),
image_dims=img_dims,
image_path=image_path,
prediction_type=CLASSIFICATION_MODEL,
prediction_type=KEYPOINT_DETECTION_MODEL,
colors=self.colors,
)

Expand Down
4 changes: 2 additions & 2 deletions roboflow/util/image_utils.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -5,8 +5,8 @@
import urllib

# Third-party imports
import pi_heif # type: ignore[import-untyped]
import pillow_avif # type: ignore[import-untyped]
import pi_heif # type: ignore[import-untyped, import-not-found]
import pillow_avif # type: ignore[import-untyped, import-not-found]
import requests
import yaml
from PIL import Image
Expand Down
3 changes: 2 additions & 1 deletion roboflow/util/prediction.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -10,6 +10,7 @@
from roboflow.config import (
CLASSIFICATION_MODEL,
INSTANCE_SEGMENTATION_MODEL,
KEYPOINT_DETECTION_MODEL,
OBJECT_DETECTION_MODEL,
PREDICTION_OBJECT,
SEMANTIC_SEGMENTATION_MODEL,
Expand Down Expand Up @@ -509,7 +510,7 @@ def create_prediction_group(json_response, image_path, prediction_type, image_di
colors = {} if colors is None else colors
prediction_list = []

if prediction_type in [OBJECT_DETECTION_MODEL, INSTANCE_SEGMENTATION_MODEL]:
if prediction_type in [OBJECT_DETECTION_MODEL, INSTANCE_SEGMENTATION_MODEL, KEYPOINT_DETECTION_MODEL]:
for prediction in json_response["predictions"]:
prediction = Prediction(
prediction,
Expand Down